Ethnicity data resource in population-wide health records: completeness, coverage and granularity of diversity

CVD-COVID-UK/COVID-IMPACT Consortium, Marta Pineda-Moncusí, Freya Allery, Antonella Delmestri, Thomas Bolton, John Nolan, Johan h. Thygesen, Alex Handy, Amitava Banerjee, Spiros Denaxas, Christopher Tomlinson, Alastair k. Denniston, Cathie Sudlow, Ashley Akbari, Angela Wood, Gary s. Collins, Irene Petersen, Laura c. Coates, Kamlesh Khunti, Daniel Prieto-SalhambraSara Khalid*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

Intersectional social determinants including ethnicity are vital in health research. We curated a population-wide data resource of self-identified ethnicity data from over 60 million individuals in England primary care, linking it to hospital records. We assessed ethnicity data in terms of completeness, consistency, and granularity and found one in ten individuals do not have ethnicity information recorded in primary care. By linking to hospital records, ethnicity data were completed for 94% of individuals. By reconciling SNOMED-CT concepts and census-level categories into a consistent hierarchy, we organised more than 250 ethnicity sub-groups including and beyond “White”, “Black”, “Asian”, “Mixed” and “Other, and found them to be distributed in proportions similar to the general population. This large observational dataset presents an algorithmic hierarchy to represent self-identified ethnicity data collected across heterogeneous healthcare settings. Accurate and easily accessible ethnicity data can lead to a better understanding of population diversity, which is important to address disparities and influence policy recommendations that can translate into better, fairer health for all.

Original languageEnglish
Article number221
Number of pages14
JournalScientific Data
Issue number1
Publication statusPublished - 22 Feb 2024


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